JWST's PEARLS: Transients in the MACS J0416.1−2403 Field
Bibliographic record
Abstract
Abstract With its unprecedented sensitivity and spatial resolution, the James Webb Space Telescope (JWST) has opened a new window for time-domain discoveries in the infrared. Here we report observations in the only field that has received four epochs (spanning 126 days) of JWST NIRCam observations in Cycle 1. This field is toward MACS J0416.1−2403, which is a rich galaxy cluster at redshift z = 0.4 and is one of the Hubble Frontier Fields. We have discovered 14 transients from these data. Twelve of these transients happened in three galaxies (with z = 0.94, 1.01, and 2.091) crossing a lensing caustic of the cluster, and these transients are highly magnified by gravitational lensing. These 12 transients are likely of a similar nature to those previously reported based on the Hubble Space Telescope (HST) data in this field, i.e., individual stars in the highly magnified arcs. However, these 12 could not have been found by HST because they were too red and too faint. The other two transients are associated with background galaxies ( z = 2.205 and 0.7093) that are only moderately magnified, and they are likely supernovae. They indicate a demagnified supernova surface density, when monitored at a time cadence of a few months to a ∼3–4 μ m survey limit of AB ∼28.5 mag, of ∼0.5 arcmin −2 integrated to z ≈ 2. This survey depth is beyond the capability of HST but can be easily reached by JWST.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".